2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)最新文献

Security of Industrial Wireless Sensor Networks: A review 工业无线传感器网络的安全:综述

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492658

S. J., Suresh Kv, D. Tandur

引用次数: 5

A comparative study of PID and SMC controller for nonlinear unmanned ground all terrain vehicle 非线性无人地面全地形车PID与SMC控制器的比较研究

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492693

Piyush N. Dave, J. Patil

引用次数: 4

Performance evaluation of star, tree & mesh optical network topologies using optimized Raman - EDFA Hybrid Optical Amplifier 基于优化Raman - EDFA混合光放大器的星形、树形和网状光网络拓扑性能评估

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492667

Rajpreet Singh, Sanjeev Dewra

{"title":"Performance evaluation of star, tree & mesh optical network topologies using optimized Raman - EDFA Hybrid Optical Amplifier","authors":"Rajpreet Singh, Sanjeev Dewra","doi":"10.1109/ITACT.2015.7492667","DOIUrl":"https://doi.org/10.1109/ITACT.2015.7492667","url":null,"abstract":"Performance at 15 Gbps of Phase Modulated signals for Star, tree and mesh optical network topologies are investigated using optimized Raman-EDFA Hybrid Optical Amplifier. Number of the users carried out is calculated by the consideration of the signal's Quality factor and received signal power. In all the three topologies, the performance is evaluated in terms of number of users at different input signal powers. In all these three topologies, the signals used are generated at 90° phase deviation. The channel spacing is taken as 0.1 THz with 1MHz line width. The minimum input signal power for all the topologies is -60 dBm. Mesh topology provides better results in terms of Quality Factor within acceptable range of 16.4621-28.9058 and provides output power 12.472dBm at each receiver whereas star topology supports 14 users within acceptable quality factor range of 7.60899-32.1223 with output signal power of 12.600dBm at each receiver and tree topology supports 16 users within acceptable quality factor range of 8.82762-9.08396 with output signal power of 12.591dBm at each receiver.","PeriodicalId":336783,"journal":{"name":"2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133349889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Bench marking of classification algorithms: Decision Trees and Random Forests - a case study using R 分类算法的基准测试:决策树和随机森林-使用R的案例研究

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492647

Manish Varma Datla

{"title":"Bench marking of classification algorithms: Decision Trees and Random Forests - a case study using R","authors":"Manish Varma Datla","doi":"10.1109/ITACT.2015.7492647","DOIUrl":"https://doi.org/10.1109/ITACT.2015.7492647","url":null,"abstract":"Decision Trees and Random Forests are leading Machine Learning Algorithms, which are used for Classification purposes. Through the course of this paper, a comparison is made of classification results of these two algorithms, for classifying data sets obtained from Kaggle's Bike Sharing System and Titanic problems. The solution methodology deployed is primarily broken into two segments. First, being Feature Engineering where the given instance variables are made noise free and two or more variables are used together to give rise to a valuable third. Secondly, the classification parameters are worked out, consisting of correctly classified instances, incorrectly classified instances, Precision and Accuracy. This process ensured that the instance variables and classification parameters were best treated before they were deployed with the two algorithms i.e. Decision Trees and Random Forests. The developed model has been validated by using Systems data and the Classification results. From the model it can safely be concluded that for all classification problems Decision Trees is handy with small data sets i.e. less number of instances and Random Forests gives better results for the same number of attributes and large data sets i.e. with greater number of instances. R language has been used to solve the problem and to present the results.","PeriodicalId":336783,"journal":{"name":"2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127331044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Multiple human tracking based on Daubechies Complex Wavelet Transform combined with histogram of templates features 基于Daubechies复小波变换结合模板直方图特征的多人跟踪

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492675

S. R, H. S. Jayanna, Ramegowda

{"title":"Multiple human tracking based on Daubechies Complex Wavelet Transform combined with histogram of templates features","authors":"S. R, H. S. Jayanna, Ramegowda","doi":"10.1109/ITACT.2015.7492675","DOIUrl":"https://doi.org/10.1109/ITACT.2015.7492675","url":null,"abstract":"In video processing, tracking objects that are in motion has attracted lot of interest of the researchers all over the world. In numerous computer vision applications, such as monitoring traffic, remote video surveillance automation, human tracking, etc, moving object detection in video sequence is the major step of knowledge extraction. In this paper, an effective human tracking system based on Daubechies Complex Wavelet Transform (DaubCxWT) combined with histogram of template is introduced. This transform is suitable to track a person in video sequences because of its approximate shift-invariance nature. Initially, DaubCxWT co-efficients associated to the person are computed. Then, in Daubechies complex wavelet domain, the energy of these co-efficients is compared to the neighbouring object, to carry out tracking in the consecutive frames. Histogram of template feature is used to extract the texture and gradient information for the human detected. Daubechies Complex Wavelet co-efficients and histogram of template features are combined to form feature vector. In order to build feature vector for every pixel in that area, the calculated co-efficients are utilised. Further, by making use of the generated feature vectors inside an adaptive search window, optimal search for the best match is performed. Search window adaption is employed to estimate the speed and direction of the person, in motion. This method has shown appreciable results.","PeriodicalId":336783,"journal":{"name":"2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)","volume":"01 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131119614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A novel approach for Sentimental Analysis and Opinion Mining based on SentiWordNet using web data 基于SentiWordNet的情感分析与意见挖掘新方法

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492646

Shoiab Ahmed, A. Danti

{"title":"A novel approach for Sentimental Analysis and Opinion Mining based on SentiWordNet using web data","authors":"Shoiab Ahmed, A. Danti","doi":"10.1109/ITACT.2015.7492646","DOIUrl":"https://doi.org/10.1109/ITACT.2015.7492646","url":null,"abstract":"Opinion mining is an art of tracking the mood of the public about a particular product or topic from a huge set of opinions or reviews publically available in web. In this work, a novel approach is proposed based on SentiWordNet, which generates count of score words into seven categories such as strong-positive, positive, weak-positive, neutral, weak-negative, negative and strong-negative words for the opinion mining task and evaluated using machine learning algorithms like Naïve Bayes, SVM and Multilayer Perception (MLP). The web data is collected using web crawler applied with different pre-processing techniques which include removal of stop-words from online reviews, then stemming is performed using Porter Stemmer algorithm, and then reviews are tagged using Stanford POS tagger. The proposed approach is experimented on movie and product web domains and obtained higher success rate in terms of accuracy measured by various tools like Kappa statistics with an accuracy of 77.7% and has lower error rates. Weighted average of different accuracy measures like Precision, Recall, TP Rate, F-Measure rate depicts higher efficiency rate and lower FP Rate for Naïve Bayes and MLP models. The experimental results of Ten-Fold cross validation on the training data shows that Naïve Bayes & MLP outperforms the SVM model. Thus, the former are used for the Sentimental Analysis of web data. The results demonstrate that the proposed novel approach has higher efficacy and it can be successfully used in Opinion Mining for the task of decision making by any web user.","PeriodicalId":336783,"journal":{"name":"2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134193868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 30

Comparative analysis of Kannada phoneme recognition using different classifiers 不同分类器对卡纳达语音位识别的比较分析

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492683

A. S., R. Kumaraswamy

{"title":"Comparative analysis of Kannada phoneme recognition using different classifiers","authors":"A. S., R. Kumaraswamy","doi":"10.1109/ITACT.2015.7492683","DOIUrl":"https://doi.org/10.1109/ITACT.2015.7492683","url":null,"abstract":"Information retrieval from audio and speech is very important in the present digital world. Phonetic search (phoneme level search) is an efficient technique for searching words or phrases from audio and speech recordings. In this paper, a baseline phoneme recognition system for Kannada language is developed using Deep Belief Networks (DBNs). Phonemes are segmented from broadcast/read mode Kannada speech. 16 MFCC features are extracted from each speech frame. These features are used as input to the recognizer. DBNs are relatively new area of machine learning. The learning procedure of DBN has two steps, an unsupervised pre-training stage and fine-tuning stage. The performance of DBN for recognition of 25 Kannada phonemes is compared with the conventional methods of speech recognition such as, Multi-Layer Feed Forward Neural Networks (ML-FFNNs) and Support Vector Machines (SVMs). Experimental results show that DBNs yield a high performance as compared to other techniques with Phoneme Error Rate (PER) of 23.6 %. In another experiment conducted, shows that DBN's performance is influenced by number of hidden units in the hidden layer chosen.","PeriodicalId":336783,"journal":{"name":"2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122954026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A rechargeable framework for improving throughput in wireless sensor network 一种提高无线传感器网络吞吐量的可充电框架

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492657

R. N, P. Tijare, M. Aparna

引用次数: 1

Post-processing methodology for word level Telugu character recognition systems using Unicode Approximation Models 使用Unicode近似模型的词级泰卢固语字符识别系统的后处理方法

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492681

N. Rani, T. Vasudev

引用次数: 3

Mobile admittance of health information with privacy and analysis in telemedicine 远程医疗中健康信息隐私的移动准入及分析

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492655

V. Arun, S. Padma, V. Shyam

引用次数: 3